Documentation for Results_With_Emissions folder

CONTENTS -- Results_With_Emissions contains three sub-directories:
1) Code : The R code to generate results -- including Figures 1-4 and S1-S11 and supplemental datasets S01-S06 in Choma, E.F., Robinson, L.A., Nadeau, K.C. Adopting electric school buses in the United States: health and climate benefits. Accepted for publication at Proceedings of the National Academy of Sciences of the United States of America.

This R code was executed in R version 4.3.2 (R Core Team, 2023) loading packages 'raster' (Hijmans et al., 2023), 'sp' (Pebesma and Bivand, 2005; 2023; Bivand et al., 2013), 'viridis' (Garnier et al., 2024), and 'TAM' (Robitzsch et al., 2022).


2) Outputs: No output is provided but this code generates Figures 1-4 and S1-S11 and supplemental datasets S01-S06 of our current paper: 
Choma, E.F., Robinson, L.A., Nadeau, K.C. Adopting electric school buses in the United States: health and climate benefits. Accepted for publication at Proceedings of the National Academy of Sciences 


3) Inputs: The data inputs used in the code. Description of each file contained in its own metadata.

3.1) Inputs provided with this deposit
a) Marginal Damages Model Outputs (which were generated as outputs from the code in the 'Marginal_Damages_Model' directory:
a.1) MV_Damages_BasePM_2017_Asthma_2019.RData
a.2) MV_Damages_BasePM_2017_Mortality_2017.RData
a.3) SRM_BasePM_2017_Asthma_2019.RData
a.4) SRM_BasePM_2017_Mortality_2017.RData
b) School_Bus_Emissions_NEI.RData
c) School_Bus_Emissions_GREET.RData
d) ESB_Deaths.RData
e) GHG_BEN.RData
f) Outputs from the code in the subdirectory 'Results_With_Emissions/SchoolDistrict_County_Mapping':
f.1) SchoolDistrict_County_Mapping.RData

Description of each file contained in its own metadata. For a) Marginal Damages Model Outputs, see a detailed documentation in the file 'Marginal_Damages_Model/Marginal_Damages_Model_Documentation.txt'

3.2) Inputs that need to be downloaded:
a) U.S. Centers for Disease Control and Prevention, NCHS Urban-Rural Classification Scheme for Counties. 
Centers for Disease Control and Prevention: National Center for Health Statistics. 
Available at: https://www.cdc.gov/nchs/data_access/urban_rural.htm (Accessed 15 June 2023). 
The data file used can downloaded at: https://www.cdc.gov/nchs/data/data_acces_files/NCHSURCodes2013.xlsx. 
This file was downloaded on 04/20/24, opened in Excel and saved as .csv.

b) U.S. Census Bureau, 2019 Cartographic Boundaries: County: 500k resolution level.
Available at: https://www2.census.gov/geo/tiger/GENZ2019/shp/cb_2019_us_county_500k.zip (Accessed 21 September 2019).


4) SchoolDistrict_County_Mapping
This directory contains the R code used to map NCES School Districts to U.S. Counties.

It contains two subdirectories
a) Code
b) Outputs

3.a) Code
R script: Results_with_Emissions/SchoolDistrict_County_Mapping/Code/SchoolDistrict_County_Mapping.R
This R code was executed in R version 4.3.2 (R Core Team, 2023)

3.b) Outputs
Saved output: Results_with_Emissions/SchoolDistrict_County_Mapping/Code/SchoolDistrict_County_Mapping.RData

Data Inputs:
It does not contain an input subdirectory because all the required data are publicly available. Five data inputs are required:

i. 2022 population by Census Block Group (2022, 5-year ACS estimates)Source: U.S. Census Bureau, 2018-2022 American Community Survey 5-Year EstimatesTable Info: ID: ACSDT5Y2022.B01001. Title: Sex by AgeAvailable at: https://data.census.gov/table/ACSDT5Y2022.B01001?t=Age%20and%20Sex&g=010XX00US$1500000Option Selected: ACS 5-Year Estimates Detailed Tables | Year 2022Downloaded on 02/19/24

ii. 2020 population by Census Block Group from the Decennial CensusSource: U.S. Census Bureau, 2020 Census Demographic and Housing Characteristics File (DHC)Table Info: ID: DECENNIALDHC2020.P1 Title: TOTAL POPULATIONAvailable at: https://data.census.gov/table/DECENNIALDHC2020.P1?q=population&g=010XX00US$1500000&tid=DECENNIALDHCAS2020.P1Option Selected: DEC Demographic and Housing Characteristics | 2020Downloaded on 02/20/24

iii. List of U.S. StatesSource: U.S. Census BureauAvailable at: https://www2.census.gov/geo/docs/reference/state.txtDownloaded on 02/19/24

iv. Connecticut: 2022 County Subdivision to 2020 Block Groups for Connecticut RelationshipSource: U.S. Census Bureau2022 County Subdivision to 2020 Block Groups for Connecticut Relationship File (acs22_cousub22_blkgrp20_st09.txt)Available at: https://www2.census.gov/geo/docs/maps-data/data/rel2022/acs22_cousub22_blkgrp20_st09.txtDownloaded on 02/20/24Documentation available at: https://www.census.gov/programs-surveys/geography/technical-documentation/records-layout/2022-connecticut-record-layout.html (accessed February 20, 2024)

v. NCES Relationship filesNational Center for Education Statistics,2023 School District Geographic Relationship Files.Available at: https://nces.ed.gov/programs/edge/data/GRF23.zipDownloaded on 02/19/24After unzipping, the file used was the file 'grf23_lea_blkgrp.xlsx'The file was opened in Excel and saved as .csv


References:

R. S. Bivand, E. Pebesma, & V. Gómez-Rubio. (2013). Applied Spatial Data Analysis with R. Springer New York. https://doi.org/10.1007/978-1-4614-7618-4

S. Garnier et al., R package “viridis”: Colorblind-Friendly Color Maps for R (Package version: 0.6.5, 2024). https://CRAN.R-project.org/package=viridis

R. J. Hijmans et al., R package “raster”: Geographic Data Analysis and Modeling (Package version: 3.6-26, 2023). https://CRAN.R-project.org/package=raster

E. Pebesma, R. Bivand, R package “sp”: Classes and Methods for Spatial Data (Package version 2.1.-2, 2023). https://CRAN.R-project.org/package=sp

E. J. Pebesma, R. S. Bivand, Classes and methods for spatial data in R. R News 5(2), 9-13 (2005). https://cran.r-project.org/doc/Rnews/Rnews_2005-2.pdf

R Core Team, R: A Language and Environment for Statistical (R version 4.3.2, 2023). R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

A. Robitzsch, T. Kiefer, M. Wu, R package “TAM”: Test Analysis Modules (Package version 4.1-4, 2022). https://CRAN.R-project.org/package=TAM